RESUMO
BACKGROUND: Tuberculosis (TB) is a major threat to public health, particularly in countries where the disease is highly prevalent, such as Ethiopia. Early diagnosis and treatment are the main components of TB prevention and control. Although the national TB guideline recommends the primary use of rapid TB diagnostics whenever feasible, there is limited evidence available that assess the efficiency of deploying various diagnostic tools in the country. Hence, this study aims to evaluate the cost-effectiveness of rapid TB/MDR-TB diagnostic tools in Ethiopia. METHODS: A hybrid Markov model for a hypothetical adult cohort of presumptive TB cases was constructed. The following TB diagnostic tools were evaluated: X-pert MTB/RIF, Truenat, chest X-ray screening followed by an X-pert MTB/RIF, TB-LAMP, and smear microscopy. Cost-effectiveness was determined based on incremental costs ($) per Disability-adjusted Life Years (DALY) averted, using a threshold of one times Gross Domestic Product (GDP) per capita ($856). Data on starting and transition probabilities, costs, and health state utilities were derived from secondary sources. The analysis is conducted from the health system perspective, and a probabilistic sensitivity analysis is performed. RESULT: The incremental cost-effectiveness ratio for X-pert MTB/RIF, compared to the next best alternative, is $276 per DALY averted, making it a highly cost-effective diagnostic tool. Additionally, chest X-ray screening followed an X-pert MTB/RIF test is less cost-effective, with an ICER of $1666 per DALY averted. Introducing X-pert MTB/RIF testing would enhance TB detection and prevent 9600 DALYs in a cohort of 10,000 TB patients, with a total cost of $3,816,000. CONCLUSION: The X-pert MTB/RIF test is the most cost-effective diagnostic tool compared to other alternatives. The use of this diagnostic tool improves the early detection and treatment of TB cases. Increased funding for this diagnostic tool will enhance access, reduce the TB detection gaps, and improve treatment outcomes.
RESUMO
BACKGROUND: HIV, tuberculosis (TB) and malaria are the three most important infectious diseases in Ethiopia, and sub-Saharan Africa. Understanding the spatial codistribution of these diseases is critical for designing geographically targeted and integrated disease control programmes. This study investigated the spatial overlap and drivers of HIV, TB and malaria prevalence in Ethiopia. METHODS: HIV, TB and malaria data were obtained from different nationwide prevalence surveys, and geospatial covariates were obtained from publicly available sources. A Bayesian model-based geostatistical framework was applied to each survey leveraging the strength of high-resolution spatial covariates to predict continuous disease-specific prevalence surfaces and their codistribution. RESULTS: The national prevalence was 1.54% (95% CI 1.40 to 1.70) for HIV, 0.39% (95% CI 0.34 to 0.45) for TB and 1.1% (95%CI 0.95 to 1.32) for malaria. Substantial subnational variation was predicted with the highest HIV prevalence estimated in Gambela (4.52%), Addis Ababa (3.52%) and Dire Dawa (2.67%) regions. TB prevalence was highest in Dire Dawa (0.96%) and Gambela (0.88%), while malaria was highest in Gambela (6.1%) and Benishangul-Gumuz (3.8%). Spatial overlap of their prevalence was observed in some parts of the country, mainly Gambela region. Spatial distribution of the diseases was significantly associated with healthcare access, demographic, and climatic factors. CONCLUSIONS: The national distribution of HIV, TB and malaria was highly focal in Ethiopia, with substantial variation at subnational and local levels. Spatial distribution of the diseases was significantly associated with healthcare access, demographic and climatic factors. Spatial overlap of HIV, TB and malaria prevalence was observed in some parts of the country. Integrated control programmes for these diseases should be targeted to these areas with high levels of co-endemicity.
